International Association of Educators   |  ISSN: 2834-7919   |  e-ISSN: 1554-5210

Original article | International Journal of Progressive Education 2020, Vol. 16(4) 204-212

Performance of Students with Different Learning Preferences in Traditional First Semester Calculus

Erhan Selcuk Haciomeroglu & Guney Haciomeroglu

pp. 204 - 212   |  DOI: https://doi.org/10.29329/ijpe.2020.268.13   |  Manu. Number: MANU-2001-12-0001.R2

Published online: August 13, 2020  |   Number of Views: 149  |  Number of Download: 542


Abstract

The present study sought to examine mathematical performance of students with different learning preferences in traditionally taught first semester calculus as well as its relationship with learning preference, spatial ability, and verbal-logical reasoning ability. Data were collected from 86 students enrolled in two sections of first semester calculus at a large state university located in the Southeastern U. S. Although the study was too small to enable generalizations, the results suggest that mathematical performance is not related to learning preference, and students do not differ in their calculus performance due to a mismatch between the instructional mode and their learning preference.

Keywords: Calculus Instruction, Calculus Performance, Spatial Ability, Verbal-Logical Reasoning Ability, Learning Preference


How to Cite this Article?

APA 6th edition
Haciomeroglu, E.S. & Haciomeroglu, G. (2020). Performance of Students with Different Learning Preferences in Traditional First Semester Calculus . International Journal of Progressive Education, 16(4), 204-212. doi: 10.29329/ijpe.2020.268.13

Harvard
Haciomeroglu, E. and Haciomeroglu, G. (2020). Performance of Students with Different Learning Preferences in Traditional First Semester Calculus . International Journal of Progressive Education, 16(4), pp. 204-212.

Chicago 16th edition
Haciomeroglu, Erhan Selcuk and Guney Haciomeroglu (2020). "Performance of Students with Different Learning Preferences in Traditional First Semester Calculus ". International Journal of Progressive Education 16 (4):204-212. doi:10.29329/ijpe.2020.268.13.

References
  1. Ben-Chaim, D., Lappan, G., & Houang, R. T. (1989). Adolescents’ ability to communicate spatial information: Analyzing and effecting students’ performance. Educational Studies in Mathematics, 20, 121-146.  [Google Scholar]
  2. Bookman, J., & Friedman, C. P. (1994). A comparison of the problem solving performance of students in lab based and traditional calculus. In E. Dubinsky, A.H. Schoenfeld, & J. Kaput (Eds.), Research in Collegiate Mathematics Education I (pp. 101-116). Providence, RI: American Mathematical Society. [Google Scholar]
  3. Bremigan, E. G. (2005). An analysis of diagram modification and construction in students’ solutions to applied calculus problems. Journal for Research in Mathematics Education, 36(3), 248-277.  [Google Scholar]
  4. Chappell, K. K., & K. Killpatrick. (2003). Effects of concept-based instruction on students’ conceptual understanding and procedural knowledge of calculus. Problems, Resources, and Issues in Mathematics Undergraduate Studies (PRIMUS), 8, 17-37. [Google Scholar]
  5. Ekstrom, R. B., French, J. W., & Harman, H. H. (1976). Manual for kit of factor-referenced cognitive tests. Princeton, NJ: Educational Testing Service. [Google Scholar]
  6. Ferrini-Mundy, J. (1987). Spatial training for calculus students: Sex differences in achievement in visualization ability. Journal for Research in Mathematics Education, 18, 126-140.  [Google Scholar]
  7. Galindo, E. (1994). Visualization in the calculus class: Relationship between cognitive style, gender, and use of technology. Unpublished doctoral dissertation, The Ohio State University. [Google Scholar]
  8. Haciomeroglu, E. S. (2012). Investigating the relationship between task difficulty and solution methods. Proceedings of the 34th Annual Conference of the North American Chapter of the International Group for the Psychology of Mathematics Education– PME-NA (pp. 202-205). Kalamazoo, Michigan. [Google Scholar]
  9. Haciomeroglu, E. S. (2015). The role of cognitive ability and preferred mode of processing in students’ calculus performance. EURASIA Journal of Mathematics, Science, & Technology Education, 11(5), 1165-1179. [Google Scholar]
  10. Haciomeroglu, E. S. (2016). Object-spatial visualization and verbal cognitive styles, and their relation to cognitive abilities and mathematical performance. Educational Sciences: Theory & Practice, 16, 987-1003.  [Google Scholar]
  11. Haciomeroglu, E. S., & Chicken, E. (2012). Visual thinking and gender differences in high school calculus. International Journal of Mathematical Education in Science and Technology, 43(3), 303-313.  [Google Scholar]
  12. Haciomeroglu, E. S., Chicken, E., & Dixon, J. (2013). Relationships between gender, cognitive ability, preference, and calculus performance. Mathematical Thinking and Learning, 15, 175-189.  [Google Scholar]
  13. Haciomeroglu, E. S., Haciomeroglu, G., Bukova-Guzel, E., & Kula, S. (2014). Pre-service teachers’ visual, analytic, and harmonic problem solving preferences for derivative and antiderivative tasks. Dicle Universitesi Ziya Gokalp Egitim Fakultesi Dergisi, 22, 108-119.  [Google Scholar]
  14. Hegarty, M., & Kozhevnikov, M. (1999). Types of visual-spatial representations and mathematical problem solving. Journal of Educational Psychology, 91, 684-689. [Google Scholar]
  15. Hughes-Hallett, D., McCallum, W. G., Gleason, A. M., Pasquale, A., Flath, D. E., Quinney, D., Lock, P. F., Raskind, W., Gordon, S. P., Rhea, K., Lomen, D. O., Tecosky-Feldman, J., Lovelock, D., Thrash, J. B., Osgood, B. G., & Tucker, T. W. (2002). Calculus: Single Variable. Danvers, MA: John Wiley & Sons, Inc.    [Google Scholar]
  16. Lean, G., & Clements, K. (1981). Spatial ability, visual imagery, and mathematical performance. Educational Studies in Mathematics, 12, 267–299.  [Google Scholar]
  17. Lowrie, T. (2001). The influence of visual representations on mathematical problem solving and numeracy performance. In J. Bobis, B. Perry, & M. Mitchelmore (Eds.), Numeracy and beyond. Proceedings of the 24th Annual Conference of the Mathematics Education Research Group of Australasia (pp. 354-361). Sydney, Australia: MERGA. [Google Scholar]
  18. Mayer, R. E., & Massa, L. (2003). Three facets of visual and verbal learners: Cognitive ability, cognitive style, and learning preference. Journal of Educational Psychology, 95, 833−841. [Google Scholar]
  19. Meel, D. E. (1998). Honors students’ calculus understandings: Comparing calculus & mathematica and traditional calculus students. In E. Dubinsky, A.H. Schoenfeld, & J. Kaput (Eds.), Research in Collegiate Mathematics Education III (pp. 163-215). Providence, RI: American Mathematical Society. [Google Scholar]
  20. Moses, B. E. (1977). The nature of spatial ability and its relationship to mathematical problem solving. Unpublished Ph.D. Dissertation, Indiana University. [Google Scholar]
  21. Park, K., & Travers, K. J. (1996). A comparative study of a computer-based and a standard college first-year calculus course. In E. Dubinsky, A. H. Schoenfeld, & J. Kaput (Eds.), Research in Collegiate Mathematics Education II (pp. 155-176). Providence, RI: American Mathematical Society. [Google Scholar]
  22. Peters, M., Laeng, B., Latham, K., Jackson, M., Zaiyouna, R., & Richardson, C. (1995). A redrawn Vandenberg and Kuse Mental Rotations Test: Different versions and factors that affect performance. Brain and Cognition, 28, 39-58. [Google Scholar]
  23. Roddick, C. D. (2001). Differences in learning outcomes: Calculus & Mathematica vs. traditional calculus. Problems, Resources, and Issues in Mathematics Undergraduate Studies (PRIMUS), 6, 161-184. [Google Scholar]
  24. Samuels, J. (2010). The use of technology in calculus instruction. Unpublished Ph.D. dissertation, Columbia University. [Google Scholar]
  25. Sternberg, R.J., Grigorenko, E. L., & Zhang, L. F. (2008). Styles of learning and thinking matter in instruction and assessment. Perspective on Psychological Science, 3(6), 486-506. [Google Scholar]
  26. Stewart, J. (2008). Calculus: Early Transcendentals. Belmont, CA: Thomson Learning, Inc.  [Google Scholar]
  27. Suwarsono, S. (1982). Visual imagery in the mathematical thinking of seventh grade students. Unpublished Ph.D. dissertation, Monash University, Melbourne, Australia. [Google Scholar]
  28. Vandenberg, S. G., & A. R. Kuse. (1978). Mental rotation, a group test of three-dimensional spatial visualisation. Perceptual Motor Skills, 47, 599-604. [Google Scholar]
  29. Windham, D. M. (2008). Faculty perceptions of a calculus reform experiment at a research university: A historical qualitative analysis. Unpublished doctoral dissertation, Florida State University. [Google Scholar]
  30. Wu, H. (1999). Basic skills versus conceptual understanding. American Educator, 23, 1-6. [Google Scholar]
  31. Wilson, R. 1997. A decade of teaching "reform calculus" has been a disaster, critics charge. Chronicle of Higher Education, 43(22): A12-A13. [Google Scholar]